Abstract 12975: Electrocardiographic Left Ventricular Hypertrophy Predicts Atrial Fibrillation Independent of Left Ventricular Anatomy
Introduction: It has been established that LVH detected by electrocardiography (ECG-LVH) and LVH detected by echocardiography (echo-LVH) carry different prognostic profiles in the prediction of cardiovascular disease events. It remains unclear whether ECG-LVH and echo-LVH are independently predictive of atrial fibrillation (AF).
Methods: This analysis included 4,904 white participants (40% male; 85% white) aged 65 years or older from the Cardiovascular Health Study who were free of baseline AF and major intraventricular conduction defects. ECG-LVH was defined by Minnesota ECG Classification criteria from baseline ECG data. Echo-LVH was defined by sex-specific left ventricular mass values >95th percentile for the study population. Incident AF events were identified during the annual study ECGs and from hospitalization discharge data. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) for the association of ECG-LVH and echo-LVH with adjudicated incident AF events, separately.
Results: ECG-LVH was detected in 224 (4.6%) participants and echo-LVH was present in 231 (4.7%) participants. Over a median follow-up of 11.9 years, a total of 1,430 AF events were detected. In a multivariable Cox model adjusted for age, sex, race, education, income, body mass index, high-density lipoprotein cholesterol, total cholesterol, smoking, systolic blood pressure, diabetes, aspirin, antihypertensive medications, valve disease, coronary heart disease, and heart failure, ECG-LVH (HR=1.44; 95%CI=1.14, 1.83) and echo-LVH (HR=1.42; 95%CI=1.11, 1.82) were independently associated with AF. When ECG-LVH (HR=1.42, 95%CI=1.12, 1.80) and echo-LVH (HR=1.40, 1.09, 1.79) were included in the same model, both were predictive of incident AF.
Conclusions: The association of ECG-LVH with AF is not dependent on abnormalities of left ventricular anatomy. These data suggest that abnormalities in cardiac electrophysiology provide a distinct profile in the prediction of AF.
Author Disclosures: N. Patel: None. W.T. O’Neal: None. S.P. Whalen: None. E.Z. Soliman: None.
- © 2016 by American Heart Association, Inc.